:orphan:
.. _install:
Installing statsmodels
======================
The easiest way to install statsmodels is to install it as part of the `Anaconda `_
distribution, a cross-platform distribution for data analysis and scientific
computing. This is the recommended installation method for most users.
Instructions for installing from PyPI, source or a development version are also provided.
Python Support
--------------
statsmodels supports Python 3.5, 3.6 and 3.7.
Anaconda
--------
statsmodels is available in through conda provided by
`Anaconda `__. The latest release can
be installed using:
.. code-block:: bash
conda install -c conda-forge statsmodels
PyPI (pip)
----------
To obtain the latest released version of statsmodels using pip:
.. code-block:: bash
conda install -c conda-forge statsmodels
Follow `this link to our PyPI page `__ to directly
download wheels or source.
For Windows users, unofficial recent binaries (wheels) are occasionally
available `here `__.
Obtaining the Source
--------------------
We do not release very often but the master branch of our source code is
usually fine for everyday use. You can get the latest source from our
`github repository `__. Or if you
have git installed:
.. code-block:: bash
git clone git://github.com/statsmodels/statsmodels.git
If you want to keep up to date with the source on github just periodically do:
.. code-block:: bash
git pull
in the statsmodels directory.
Installation from Source
------------------------
You will need a C compiler installed to build statsmodels. If you are building
from the github source and not a source release, then you will also need
Cython. You can follow the instructions below to get a C compiler setup for
Windows.
If your system is already set up with pip, a compiler, and git, you can try:
.. code-block:: bash
pip install git+https://github.com/statsmodels/statsmodels
If you do not have pip installed or want to do the installation more manually,
you can also type:
.. code-block:: bash
python setup.py install
Or even more manually
.. code-block:: bash
python setup.py build
python setup.py install
statsmodels can also be installed in `develop` mode which installs statsmodels
into the current python environment in-place. The advantage of this is that
edited modules will immediately be re-interpreted when the python interpreter
restarts without having to re-install statsmodels.
.. code-block:: bash
python setup.py develop
Compilers
~~~~~~~~~
Linux
^^^^^
If you are using Linux, we assume that you are savvy enough to install `gcc` on
your own. More than likely, its already installed.
Windows
^^^^^^^
It is strongly recommended to use 64-bit Python if possible.
Getting the right compiler is especially confusing for Windows users. Over time,
Python has been built using a variety of different Windows C compilers.
`This guide `_ should help
clarify which version of Python uses which compiler by default.
Mac
^^^
Installing statsmodels on MacOS will requires installing `gcc` which provides
a suitable C compiler. We recommend installing Xcode and the Command Line
Tools.
Dependencies
------------
The current minimum dependencies are:
* `Python `__ >= 3.5
* `NumPy `__ >= 1.14
* `SciPy `__ >= 1.0
* `Pandas `__ >= 0.21
* `Patsy `__ >= 0.5.0
Cython is required to build from a git checkout but not to run or install from PyPI:
* `Cython `__ >= 0.29 is required to build the code from
github but not from a source distribution.
Given the long release cycle, statsmodels follows a loose time-based policy for
dependencies: minimal dependencies are lagged about one and a half to two
years. Our next planned update of minimum versions is expected in the first
half of 2020.
Optional Dependencies
---------------------
* `Matplotlib `__ >= 2.2 is needed for plotting
functions and running many of the examples.
* If installed, `X-12-ARIMA `__ or
`X-13ARIMA-SEATS `__ can be used
for time-series analysis.
* `pytest `__ is required to run
the test suite.
* `IPython `__ >= 5.0 is required to build the
docs locally or to use the notebooks.
* `joblib `__ >= 0.9 can be used to accelerate distributed
estimation for certain models.
* `jupyter `__ is needed to run the notebooks.